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Diffusion model on the spread of new technology

Link:

http://knowledge.wharton.upenn.edu/article/can-innovation-spread-faster-through-social-networks/

 

With the increasing prominence of social networks, there has been an observed behavioral pattern in how an individual’s choices depend on what other people do. Professor Valentina Assenova of Wharton examines this in her latest research paper, titled “Modeling the Diffusion of Complex Innovations as a Process of Opinion Formation Through Social Networks.” As delineated in her paper, such behavior is clearly present in the introduction of new and unproven technology, or new products and services that aren’t obviously good or bad yet to the public. Inspired by the spread of microfinance, which is a complex innovation with mixed evidence about its benefits, Professor Assenova analyzes the diffusion of technology or products with such property within populations and the relevant factors that play a role in how the technology spreads based on the opinions of others.

The paper is a theoretical model that utilizes a DeGroot naive learning model that tests the spread of microfinance. There are several different features of this model that proved significance, one of them being density, or how connected people are to others, and another being asymmetry of individual relationships, or whether person A is more likely to influence person B than B to A. The tests found that networks with both high density and high asymmetry are ideal/optimal for diffusion of complex innovations, as spread is more likely when there are a lot of people in a cluster with only a few people whose opinions heavily outweigh the opinions of the rest. By applying these results and patterns to real-world applications, advertisement approaches can target specific groups using specific methods to maximize adoption of a product.

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